Inverse planned intensity modulated radiotherapy(IMRT) fields can be highly modulated due to the large number of degrees of freedom involved in the inverse planning process. Additional modulation typically results in a more optimal plan, although the clinical rewards may be small or offset by additional delivery complexity and/or increased dose from transmission and leakage. Increasing modulation decreases delivery efficiency, and may lead to plans that are more sensitive to geometrical uncertainties. The purpose of this work is to assess the use of maximum intensity limits in inverse IMRT planning as a simple way to increase delivery efficiency without significantly affecting plan quality. Nine clinical cases (three each for brain, prostate, and head/neck) were used to evaluate advantages and disadvantages of limiting maximum intensity to increase delivery efficiency. IMRT plans were generated using in-house protocol-based constraints and objectives for the brain and head/neck, and RTOG 9406 dose volume objectives in the prostate. Each case was optimized at a series of maximum intensity ratios (the product of the maximum intensity and the number of beams divided by the prescribed dose to the target volume), and evaluated in terms of clinical metrics, dose-volume histograms, monitor units (MU) required per fraction (SMLC and DMLC delivery), and intensity map variation (a measure of the beam modulation). In each site tested, it was possible to reduce total monitor units by constraining the maximum allowed intensity without compromising the clinical acceptability of the plan. Monitor unit reductions up to 38% were observed for SMLC delivery, while reductions up to 29% were achieved for DMLC delivery. In general, complicated geometries saw a smaller reduction in monitor units for both delivery types, although DMLC delivery required significantly more monitor units in all cases. Constraining the maximum intensity in an inverse IMRT plan is a simple way to improve delivery efficiency without compromising plan objectives.

In this paper the radiological properties of a compensator material consisting of wax and gypsum is presented. Effective attenuation coefficients (EACs) have been determined from transmission measurements with an ion chamber in a Perspex phantom. Measurements were made at 80 and 100 cm source-to-skin distance (SSD) for beam energies of 6, 8, and 15 MV, for field sizes ranging from narrow beam geometries up to , and at measurement depths of maximum dose build-up, 5 and 10 cm. A parametrization equation could be constructed to predict the EAC values within 4% uncertainty as a function of field size and depth of measurement. The EAC dependence on off-axis position was also quantified at each beam energy and SSD. It was found that the compensator material reduced the required thickness for compensation by 26% at 8 MV when compared to pure paraffin wax for a field. Relative surface ionization (RSI) measurements have been made to quantify the effect of scatteredelectrons from the wax–gypsum compensator. Results indicated that for 80 cm SSD the RSI would exceed 50% for fields larger than . At 100 cm SSD the RSI values were below 50% for all field sizes used.

A procedure has been developed for automating optimal selection of sources from an available inventory for the low dose rate brachytherapy, as a replacement for the conventional trial-and-error approach. The method of optimized constrained ratios was applied for clinical source selection for intracavitary Cs-137 implants using Varian BRACHYVISION software as initial interface. However, this method can be easily extended to another system with isodose scaling and shaping capabilities. Our procedure provides optimal source selection results independent of the user experience and in a short amount of time. This method also generates statistics on frequently requested ideal source strengths aiding in ordering of clinically relevant sources

Detector systems using plastic scintillators can provide instantaneous measurements with high spatial resolution in many applications including small field and high dose gradient field applications. Energy independence and water equivalence are important dosimetric properties that determine whether a detector will be useful in a clinical setting. Using Monte Carlo simulations, we calculated the energy dependence of plastic scintillators when exposed to photon beams in the radiotherapeutic range. These calculations were performed for a detector comprised of a BC-400 plastic scintillator surrounded by a polystyrene wall. Our results showed the plastic scintillation detector to be nearly energy independent over a range of energies from . The ratio of the dose absorbed by the scintillator to that absorbed by water was nearly a constant, approximately equal to 0.98 over the entire energy range of interest. These results confirm the water equivalence of the plastic scintillation detector and are in very good agreement with earlier results obtained using Burlin cavity theory.

The purpose of the present study is to characterize electron contamination in photonbeams in different clinical situations. Variations with field size,beam modifier (tray, shaping block) and source–surface distance (SSD) were studied. Percentage depth dosemeasurements with and without a purging magnet and replacing the air by helium were performed to identify the two electron sources that are clearly differentiated: air and treatment head. Previous analytical methods were used to fit the measured data, exploring the validity of these models. Electrons generated in the treatment head are more energetic and more important for larger field sizes, shorter SSD, and greater depths. This difference is much more noticeable for the beam than for the beam. If a tray is used as beam modifier, electron contamination increases, but the energy of these electrons is similar to that of electrons coming from the treatment head. Electron contamination could be fitted to a modified exponential curve. For machine modeling in a treatment planning system, setting SSD at for input data could reduce errors for most isocentric treatments, because they will be delivered for SSD ranging from . For very small field sizes, air-generated electrons must be considered independently, because of their different energetic spectrum and dosimetric influence.

A time delay in a respiratory gating system could cause an unexpected phase mismatch for synchronized gating radiotherapy. This study presents a method of identifying and measuring the time delay in a gating system. Various port films were taken for a motion phantom at different gating window levels with a very narrow window size. The time delay for the gating system was determined by comparing the motion curve (the position of a moving object versus the gating time) measured in the port films to the motion curve determined by the video cameras. The measured time delay for a linac-based gating system was . This time delay could induce target missing if it was not properly taken into account for the synchronized gating radiotherapy. Measurement/verification of the time delay should be considered as an important part of the accepting/commissioning test before the clinical use of the gating system.

Helical tomotherapy (HT) requires a method of accurately determining the absorbed dose under reference conditions. In the AAPM’s TG-51 external beam dosimetry protocol, the quality conversion factor, , is presented as a function of the photon component of the percentage depth-dose at 10 cm depth, , measured under the reference conditions of a field size and a source-to-surface distance (SSD) of 100 cm. The value of from HT cannot be used for the determination of because the design of the HT does not meet the following TG-51 reference conditions: (i) the field size and the practical SSD required by TG-51 are not obtainable and (ii) the absence of the flattening filter changes the beam quality thus affecting some components of . The stopping power ratio is not affected because of its direct relationship to . We derive a relationship for the Exradin A1SL ion chamber converting the measured under HT “reference conditions” of and a field-size , to the dosimetric equivalent value under for TG-51 reference conditions for HT. This allows the determination of under the HT reference conditions. The conversion results in changes of 0.1% in the value of for our particular unit. The conversion relationship should also apply to other ion chambers with possible errors on the order of 0.1%.

With intensity-modulated radiotherapy(IMRT), a variety of user-defined dose distribution can be produced using inverse planning. The generalized equivalent uniform dose (gEUD) has been used in IMRToptimization as an alternative objective function to the conventional dose-volume-based criteria. The purpose of this study was to investigate the effectiveness of gEUD optimization to fine tune the dose distributions of IMRT plans. We analyzed the effect of gEUD-based optimization parameters on plan quality. The objective was to determine whether dose distribution to selected structures could be improved using gEUD optimization without adversely altering the doses delivered to other structures, as in sculpting. We hypothesized that by carefully defining gEUD parameters ( and ) based on the current dose distributions, the optimization system could be instructed to search for alternative solutions in the neighborhood, and we could maintain the dose distributions for structures already satisfactory and improve dose for structures that need enhancement. We started with an already acceptable IMRT plan optimized with any objective function. The dose distribution was analyzed first. For structures that dose should not be changed, a higher value of was used and was set slightly higher/lower than the EUD value at the current dose distribution for critical structures/targets. For structures that needed improvement in dose, a higher to medium value of was used, and was set to the EUD value or slightly lower/higher for the critical structure/target at the current dose distribution. We evaluated this method in one clinical case each of head and neck, lung and prostate cancer.Dose volume histograms, isodose distributions, and relevant tolerance doses for critical structures were used for the assessment. We found that by adjusting gEUD optimization parameters, the dose distribution could be improved with only a few iterations. A larger value of could lead to faster convergence and a medium value of could result in a search in a broader area. Such improvement could also be achieved by optimization based on other criteria, but the gEUD-based method has the advantage of efficiency and flexibility. Therefore, gEUD-based optimization can be used as a tool to improve IMRT plans by adjusting the planning parameters, thereby making dose sculpting feasible.

Inherent to helical tomotherapy is a dose variation pattern that manifests as a “ripple” (peak-to-trough relative to the average). This ripple is the result of helical beam junctioning, completely unique to helical tomotherapy. Pitch is defined as in helical CT, the couch travel distance for a complete gantry rotation relative to the axial beam width at the axis of rotation. Without scattering or beam divergence, an analytical posing of the problem as a simple integral predicts minima near a pitch of where is an integer. A convolution-superposition dose calculator (TomoTherapy, Inc.) included all the physics needed to explore the ripple magnitude versus pitch and beam width. The results of the dose calculator and some benchmark measurements demonstrate that the ripple has sharp minima near . The 0.86 factor is empirical and caused by a beam junctioning of the off-axis dose profiles which differ from the axial profiles as well as a long scatter tail of the profiles at depth. For very strong intensity modulation, the 0.86 factor may vary. The authors propose choosing particular minima pitches or using a second delivery that starts 180 deg off-phase from the first to reduce these ripples: “Double threading.” For current typical pitches and beam widths, however, this effect is small and not clinically important for most situations. Certain extremely large field or high pitch cases, however, may benefit from mitigation of this effect.

Quality assurance (QA) procedures for intensity modulation radiation therapy (IMRT) usually involve an ion chamber measurement in a phantom using the beam configuration of the actual treatment plan. In our QA procedures it was observed that the degree of agreement between the measurement and the calculation could vary from plan to plan, from linac to linac, as well as over time, with a discrepancy up to 8%. In this paper we examine one aspect of the process which can contribute to such poor reproducibility, namely, the leaf end position accuracy. A series of measurements was designed to irradiate an ion chamber using small beam segments where one multileaf collimator(MLC) edge covers half of the chamber. It was shown that the reproducibility varied up to 13%, which provides a possible explanation for the observed discrepancies above. A useful tool was also developed to measure ionization signals from individual segments of an IMRT sequence. In addition, an understanding of the leaf end position variations offers some insight into the overall quality of an IMRT dose distribution.

CTscanners acquire noisy data at discrete sample positions. Typically, a convention of how to continue these data from discrete integer positions to the continuous domain must be applied during processing. We study the properties of three typical one-dimensional spatial domain interpolation algorithms in terms of a cost or quality factor . This figure of merit is a function of spatial resolution, data noise, and dose and is used to optimize detector design. Spatial resolution is defined as either mean square width or as the full width at half maximum of the point spread function (PSF). Our results show that a trapezoidal interpolation algorithm is optimal for the high resolution domain (relative to the detector aperture size ) and should be replaced by a triangular or Gaussian interpolation function for spatial resolutions of about or larger; these result in bell-shaped PSFs. Assuming such a hybrid algorithm we find a 1.5-fold increase of —this is equivalent to 50% improved dose usage—when smoothing the data to a spatial resolution of or more compared to a highest resolution reconstruction. Therefore it is advisable to use detectors of one-third of the size of the desired spatial resolution and to compensate for the 1.5-fold increase in by reducing dose by 33%. Under the presence of moderately sized septa (e.g., 10% of the spatial resolution element size) the benefit of optimizing still lies in the order of 30% improved dose usage; in that case the detector size should be on the order of and a dose reduction of 23% can be achieved. Again, bell-shaped PSFs show a better tradeoff between noise and resolution for a given dose than rectangular-shaped PSFs. The general interpretation of our results is that the degree of freedom of choosing the weighting or interpolation function for a given resolution is large for small detectors and small for large detectors. Thus systems with small have a higher potential of optimization compared to systems with large . Similarly, detector binning, which corresponds to replacing by , should be avoided. Note that the figures reported correspond to a one-dimensional interpolation. Two-dimensional detectors typically separate and resulting quality factors can be easily obtained by multiplication. Then, is expected to improve by a factor of without septa and by a factor of with septa. This indicates that dose can be reduced by about 56% and about 41%, respectively. Our findings are general and not restricted to CT. They can be readily applied to medical or nonmedical imaging devices and digital detectors and they may also turn out to be useful in other fields.

Deformable shape models (DSMs) comprise a general approach that shows great promise for automatic image segmentation. Published studies by others and our own research results strongly suggest that segmentation of a normal or near-normal object from 3D medical images will be most successful when the DSM approach uses (1) knowledge of the geometry of not only the target anatomic object but also the ensemble of objects providing context for the target object and (2) knowledge of the image intensities to be expected relative to the geometry of the target and contextual objects. The segmentation will be most efficient when the deformation operates at multiple object-related scales and uses deformations that include not just local translations but the biologically important transformations of bending and twisting, i.e., local rotation, and local magnification. In computer vision an important class of DSM methods uses explicit geometric models in a Bayesian statistical framework to provide a priori information used in posterior optimization to match the DSM against a target image. In this approach a DSM of the object to be segmented is placed in the target image data and undergoes a series of rigid and nonrigid transformations that deform the model to closely match the target object. The deformation process is driven by optimizing an objective function that has terms for the geometric typicality and model-to-image match for each instance of the deformed model. The success of this approach depends strongly on the object representation, i.e., the structural details and parameter set for the DSM, which in turn determines the analytic form of the objective function. This paper describes a form of DSM called m-reps that has or allows these properties, and a method of segmentation consisting of large to small scale posterior optimization of m-reps. Segmentation by deformable m-reps, together with the appropriate data representations, visualizations, and user interface, has been implemented in software that accomplishes 3D segmentations in a few minutes. Software for building and training models has also been developed. The methods underlying this software and its abilities are the subject of this paper.

Analysis of detective quantum efficiency (DQE) is an important component of the investigation of imaging performance for flat-panel detectors(FPDs). Conventional descriptions of DQE are limited, however, in that they take no account of anatomical noise (i.e., image fluctuations caused by overlying anatomy), even though such noise can be the most significant limitation to detectability, often outweighing quantum or electronic noise. We incorporate anatomical noise in experimental and theoretical descriptions of the “generalized DQE” by including a spatial-frequency-dependent noise-power term, , corresponding to background anatomical fluctuations. Cascaded systems analysis (CSA) of the generalized DQE reveals tradeoffs between anatomical noise and the factors that govern quantum noise. We extend such analysis to dual-energy (DE) imaging, in which the overlying anatomical structure is selectively removed in image reconstructions by combining projections acquired at low and high kVp. The effectiveness of DE imaging in removing anatomical noise is quantified by measurement of in an anthropomorphic phantom. Combining the generalized DQE with an idealized task function to yield the detectability index, we show that anatomical noise dramatically influences task-based performance, system design, and optimization. For the case of radiography, the analysis resolves a fundamental and illustrative quandary: The effect of kVp on imaging performance, which is poorly described by conventional DQE analysis but is clarified by consideration of the generalized DQE. For the case of DE imaging, extension of a generalized CSA methodology reveals a potentially powerful guide to system optimization through the optimal selection of the tissue cancellation parameter. Generalized task-based analysis for DE imaging shows an improvement in the detectability index by more than a factor of 2 compared to conventional radiography for idealized detection tasks.

The purpose of this study is to describe and evaluate a new analytical model for Varian enhanced dynamic wedge factors at off-center points. The new model was verified by comparing measured and calculated wedge factors for the standard set of wedge angles (i.e., 15°, 30°, 45° and 60°), different symmetric and asymmetric fields, and two different photon energies. The maximum difference between calculated and measured wedge factors is less than 2%. The average absolute difference is within 1%. The obtained results indicate that the suggested model can be useful for independent dose calculation with enhanced dynamic wedges.

In this work, a new method of analyzing noninvasive reflection spectra is presented. The approach explicitly models the inhomogeneity of chromophore distributions in living tissues and thus extracts not only apparent chromophore concentrations but also relative chromophore distributions in tissues. Furthermore, it works with spectra obtained with short source-detector separations where the diffusion theory of light transport through turbid media is not valid, and formerly presented methods thus fail. The effect of inhomogeneously distributed chromophores in a multicompartment model of tissues on measuredreflection spectra is explained and an algorithm to deconvolute tissuespectra based on this model is presented. It is evaluated using simulated spectra and measurements on phantoms, which are made up of partially printed pieces of paper to simulate inhomogeneous dye distributions. Its applicability to real tissue is proven using reflection spectra obtained with 130 μm source-detector separation from a hemoperfusion stop experiment. The proposed model accurately determines apparent chromophore concentrations and corresponding distributions in simulated spectra and phantoms. Regarding real tissuespectra, the results correspond to former publications and the spectral reconstruction yields only minimal residuals, indicating a complete and accurate spectral deconvolution. In conclusion, the presented approach is a suitable extension and amendment to existing models of light transport through inhomogeneous samples.

Ultrasound imaging is widely used in medicine because of its benign characteristics and real-time capabilities. Physics theory suggests that the application of tomographic techniques may allow ultrasound imaging to reach its full potential as a diagnostic tool allowing it to compete with other tomographic modalities such as x-ray computer tomography, and MRI. This paper describes the construction and use of a prototype tomographic scanner and reports on the feasibility of implementing tomographic theory in practice and the potential of ultrasound(US)tomography in diagnostic imaging. Data were collected with the prototype by scanning two types of phantoms and a cadaveric breast. A specialized suite of algorithms was developed and utilized to construct images of reflectivity and sound speed from the phantom data. The basic results can be summarized as follows. (i) A fast, clinically relevant UStomographyscanner can be built using existing technology. (ii) The spatial resolution, deduced from images of reflectivity, is . The demonstrated depth-of-field is superior to that of conventional ultrasound and the image contrast is improved through the reduction of speckle noise and overall lowering of the noise floor. (iii) Images of acoustic properties such as sound speed suggest that it is possible to measure variations in the sound speed of . An apparent correlation with x-ray attenuation suggests that the sound speed can be used to discriminate between various types of soft tissue. (iv) Ultrasoundtomography has the potential to improve diagnostic imaging in relation to breast cancer detection.

Recent clinical trials show promising results in using MRI and MRI-based thermometry to guide focused ultrasound surgery to treat uterine fibroids. During treatment, large variation in the focal temperature distribution has been observed. It is possible that some of this variation is due to abdominal tissue inhomogeneity, which might be causing focal beam distortion, and might largely decrease the focusing ability in deep-seated tissues. The purpose of this study was to numerically demonstrate this effect and also show the feasibility of restoring the focal beam patterns by employing the phase correction procedure for phased arrays. Abdominal MR data from four uterine fibroid patients were obtained to reconstruct the three-dimensional meshes of interfaces used in simulations, and one patient was selected to perform the analysis of key parameters in focused ultrasound surgery. Results show that, without phase correction, the focused beam can be severely distorted while using a frequency above or delivering ring-shape focal patterns. Different focal positions at the same depth may require a different power to induce the same ultrasonic intensity level (up to 179% among the different focal patterns). After adding a phase correction procedure, the distorted focal beams can be restored, and the peak intensity can be largely recovered (up to 85% among the different focal patterns). This study may offer important implications and information for treatment planning toward optimizing focused ultrasound surgery in uterine fibroid or other abdominal tumor treatments.